- Adding a new bedroom measuring 130 sq. ft.
- Adding a new half bathroom measuring 80 sq. ft.
- Expanding the living room by 400 sq. ft.
Predictions were made using generated data based on Lasso Regression. Because this is a simple linear regression without any interaction, three options would cause linear changes in log(sale price).
I assumed that those new modifications would be above grade and such changes would not change the overall quality of the hosue. However, addtional inforamtion on whether the modification was above grade or in the basement, whether it would add a fireplace, as well as heating would increase prediction accuracy.
- Convert the home into a duplex and rent both units.
- Rent the home as is.
- Sell the home for market value.
There are 178 data points from the sample dataset that are single-family housing with 4 bedrooms.
It is quite straight forward to calculate the yearly rent.
For conversion to duplex estimation, I divided most of the numerical varaibles by 2 then predicted the sale price using the Lasso model developed earlier. In general, categorical variables and condition related variables were kept as it is.